Finding the Next Unicorn: When Big Data Meets Venture Capital

Abstract

Venture capital (VC) has been growing rapidly in recent years. So far the screening and evaluation of potential startups as investment objects largely depends on the venture capitalist's personal experience, network and qualitative evaluations. In the era of big data, the advent of new data sources and analytic techniques enables a data-driven investment process. Grounded in systems theory and the theory of complementarity, this study reports the findings from an exploratory study of 13 VC firms that synthesize and use novel data sources. Our analysis shows that the data-driven approach, in particular, impacts the deal origination and screening stages of investment. It leads to informational and transactional benefits, which lower operational costs in the short term and enlarge the potential return on investment of a VC firm in the long term. We contribute to the literature by shedding light on how various data sources complementarily lead to additional business value.

Data Anonymization as Instrument to manage Knowledge Risks in Supply Chains

“…Generally, the usage of BDA has a potential to increase an organization's process performance. Various organizational processes were found to be improved by BDA, for instance delivery processes (Grover et al, 2018), palletizing processes in the air cargo domain (Mazur et al, 2022), and investment processes in the venture capital sector (Weibl & Hess, 2019). More concretely, process efficiency was increased significantly.…”

“…More concretely, process efficiency was increased significantly. Efficiency gains especially concern the temporal dimension of process execution (Eggers et al, 2021;Weibl & Hess, 2019). As stated by Du et al (2020), the application of BDA shortens "the average production cycle from 9 to 5 days" (p. 130).…”

“…Increased Process Efficiency [13,15,18,25,26,27,32,34] 8 Increased Productivity [5,9,26] 3 Improved Resource Utilization [13,17,18,31,33] 5 Reduced Waste [29] 1 Increased Process Performance [2,15,17,18,25,27,28,31,34,37] 10 Firm & Organization Performance Improved Organizational Performance [6,13,22,26,32] 5…”

“…Increased Competitive Advantage [5,7,11,14,21] 5 Increased Market Value [5] 1 Improved Market Perception [17] 1 Improved Inter-Organizational Collaboration [13,27,34] 3 Improved Supply Chain Performance [10] 1…”

Cost‐sensitive machine learning to support startup investment decisions

“…AI is revolutionizing decision‐making in various financial sectors, like credit assessment, quantitative trading, risk management, fraud detection, and stock trading (Castleman, 2020) and is predicted to have a transformational impact on financial services while enhancing decision accuracy (Ryll et al, 2020). However, venture capitalists have shown reluctance in adopting AI within their investment decisions, instead continuing to rely heavily on personal networks and subjective instincts tainted by various biases and subjective judgment (Sheehan & Sheehan, 2017; Weibl & Hess, 2019). For individual investors participating in equity crowdfunding, the decision‐making process is even more limited.…”